Objectives
- Explain the core principles, terminology and governing standards of Machine Learning
- Apply proven methods and tools for Machine Learning to real workplace situations
- Analyse performance data to find risks, gaps and improvement opportunities
- Compare your practice with international benchmarks and regional case studies
- Build a practical action plan to apply Machine Learning in your organisation
Who should attend
Professionals and leaders preparing their teams for AI, automation and new ways of working.
Course outline — 5 days
- Day 1Principles, terminology and governing standardsMachine Learning
- Day 2Methods, tools and calculationsMachine Learning
- Day 3Operation, inspection and performanceMachine Learning
- Day 4Risk, troubleshooting and case studiesMachine Learning
- Day 5Best practice, assessment and action planMachine Learning
10-day outline
- Day 1Principles, terminology and governing standardsMachine Learning
- Day 2Methods, tools and calculationsMachine Learning
- Day 3Operation, inspection and performanceMachine Learning
- Day 4Risk, troubleshooting and case studiesMachine Learning
- Day 5Best practice review and mid-course assessmentMachine Learning
- Day 6Advanced analysis techniquesMachine Learning
- Day 7Digital tools, data and softwareMachine Learning
- Day 8Practical labs and simulationsMachine Learning
- Day 9Regional benchmarks and lessons learnedMachine Learning
- Day 10Capstone project and final assessmentMachine Learning
Upcoming sessions 2027–2030
| City | Dates | Duration |
|---|---|---|
| Munich | 24 Jan 2028 – 28 Jan 2028 | 5 days |
| Jeddah | 11 Feb 2029 – 15 Feb 2029 | 5 days |
| Jeddah | 6 May 2029 – 17 May 2029 | 10 days |
| Abu Dhabi | 24 Jun 2029 – 28 Jun 2029 | 5 days |
| Geneva | 1 Apr 2030 – 5 Apr 2030 | 5 days |
| Sharjah | 23 Jun 2030 – 27 Jun 2030 | 5 days |
No public session is listed yet. We can run this course in any city on your dates, online, or at your company.